Papers by Yaxuan Qin

1 papers
TAGCOS: Task-agnostic Gradient Clustered Coreset Selection for Instruction Tuning Data (2025.findings-naacl)

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Challenge: Existing methods for instruction tuning are limited due to the increasing volume of instruction datasets and the increased computational costs.
Approach: They propose to extract a small and highly informative subset of training samples from a large dataset that achieves comparable performance to the full dataset.
Outcome: The proposed algorithm outperforms other unsupervised methods and achieves comparable performance to the full dataset.

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